Method of controlling waste water purification plants using multiple control functions

ABSTRACT

A method of automatically controlling a wastewater purification plant comprises the steps of measuring two or more of a number of parameters, determining a control parameter on the basis of the measurement results obtained and at least two selected control functions, selecting a control action on the basis of the determined control parameter and subsequently implementing the selected control action.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to a method of automatically controlling awaste water purification plant wherein one or more of a number of systemparameters are measured, a control parameter on the basis of themeasurement results obtained and a selected control function aredetermined, a control action on the basis of the determined control isselected parameter, and the selected control action is implemented.

2. The Prior Art

In a prior art method of the type mentioned above, control is effectedof biological waste water plants, wherein it is desired to carry out amicrobial removal of the nitrogen and phosphorous containing compoundsas well as organic matter.

A variety of embodiments of such biological purification plants areknown, but they generally have the common feature that they comprise anitrification tank or zone operated in aerobic conditions, adenitrification tank or zone operated in anoxic conditions and aclarification tank in which a sedimentation of active sludge is carriedout and from which tank part of the active sludge is generally recycledto the nitrification and/or denitrification tank.

The above-mentioned group of purification plant types comprises two maintypes, viz. plants wherein recycling of completely or partially treatedwaste water is effected and plants comprising two treatment tanks whichare alternately operated in anoxic and aerobic conditions, and in whichplants no recycling of completely or partially treated waste water iseffected.

In the prior art method an initial measurement is carried out of a givenparameter, such as the oxygen concentration and the ammoniumconcentration, in the aerobic tank. On the basis of the measurementresult obtained the state of the aerobic tank is identified, andsubsequently the identified plant state and a preselected controlcriterium, e.g., maintenance of the oxygen concentration in the aerobictank at a desired level, form the basis of a selection of a controlaction, e.g., in the form of a change in the oxygen supply rate.

Identification of the plant state is effected by means of a mathematicalmodel for the relevant purification process quantitatively describingthe correlation between the various measurement parameters.

The mathematical model allows i.a. control carried out using a givencontrol criterium related to a specific measurement parameter, to becarried out on the basis of a measurement of another parameter, e.g. theoxygen set point may be controlled on the basis of a measurement of theammonium concentration.

In another prior art method of the type described above, control iseffected on the basis of measurement results for one of two or moremeasurement parameters. Priorities are given to the individualmeasurement parameters on the basis of their information value,suitability and credibility, and in normal conditions control iseffected on the basis of measurement results for the measurementparameter of first priority.

If, for a period of time, it is impossible to obtain measurement resultsfor the measurement parameter of first priority, or in case themeasurement results obtained are considered erroneous and therefore haveto be rejected, control is instead effected on the basis of themeasurement parameter of second priority etc. This is generally known asa priority sequence of control criteria.

In a third prior art control method, control is carried out usingmeasurements for two or more parameters simultaneously. In this controlmethod, the measurement result of one parameter, e.g., the ammoniumconcentration, is used to determine the desired value (the set point) ofa second parameter, e.g., the oxygen concentration. The fixed set pointof the second parameter is then compared to a measurement of saidparameter carried out simultaneously with the measurement of the firstparameter, and on the basis of the said comparison a control action isthen selected for the change of the second parameter from the measuredvalue to the set point value. Such control method is generally known asa cascade control.

"Computer Control of an Alternating Activated Sludge Process", Kummel M.and Nielsen M. K., published at The International Symposium on ProcessSystems Engineering, Kyoto, August 23-27, 1982, discloses a method ofcontrolling a biological purification plant comprising two treatmenttanks which are alternately operated in anoxic and aerobic conditions,and wherein the flow pattern is changed accordingly and so that theuntreated waste water is supplied to the anoxic tank, from which it iscarried to the aerobic tank and therefrom further on in the plant to aclarification tank in which a sedimentation of active sludge is carriedout, which sludge is subsequently recycled in the plant for introductioninto the anoxic tank, and from which clarification tank the effluent isdischarged.

The control is effected by means of a computer collecting themeasurement results, analyzing the results on the basis of amathematical model and implementing new control strategies.

In the prior art method, measurements of oxygen, ammonium and nitrateare carried out using suitable sensors, the control parameters usedbeing the oxygen supply rate and the nitrification and denitrificationperiod ratio.

In the prior art method, the ammonium and nitrate concentration methodsare used continuously to determine the corresponding optimum oxygenconcentration (the set point) during the nitrification anddenitrification processes, respectively.

Furthermore the nitrification and denitrification period ratio iscontrolled relative to the ammonium content of the untreated wastewater, i.e., such that the nitrification period is prolonged when theammonium load is high and shortened when the ammonium load is low, andvice versa for the denitrification period.

EP-A-0,446,036 discloses an apparatus for controlling a system, e.g. awaste water purification plant, the apparatus:comprising 1) a number ofmeasuring units, 2) means for analysing measurement data in order toselect a characteristic data set, 3) means for analysing thecharacteristic data set in order to identify a possible operationproblem, 4) means for analysing the operation problem in order to find astrategy for resolution of the problem, and 5) means for controlling thesystem on the basis of the strategy.

SUMMARY OF THE INVENTION

Use of the means for analysing the operation problem includes a strategydetermination mechanism, wherein measurement results for a number ofparameters are used as input data to a neural network, and theinformation contained in the output data from the neural network is usedas a basis for determining a set of setpoints for the controlparameters.

It is the object of the present invention to provided method of the typedescribed which provides a more efficient, and accurate control than theprior art methods.

The method according to the invention is characterized in that thecontrol parameter is determined on the basis of the measurement resultsfor at least two parameters and the control functions associated withsaid parameters.

The invention is based on the discovery that some of the parametersmeasured during the control of a waste water purification plant provideinformation about the same physical conditions, and that consequentlysuch parameters may be used to obtain a more accurate, quick andreliable identification of the state of the plant and determination ofthe control parameter, thereby resulting in a more efficient control ofthe plant.

Furthermore, the use of the method according to the invention allows animproved utilization of the capacity of the purification plant.

In addition it is possible to identify variations in the amount andconcentration of polluting substances in the waste water supplied to theplant more quickly than with the prior art methods, and consequently amore efficient control is obtained.

As used herein the term "control function" means the function accordingto which a given control parameter according to a mathematical model ofthe deterministic/stocastic type is determined relative to a givenmeasurement parameter or a parameter derived therefrom, i.e. the controlfunction defines the correlation between the control parameter and themeasurement parameter or the parameter derived therefrom.

The control functions used according to the invention are preferabledetermined on the basis of past data and experience from earlieroperations.

The control functions used are typically discontinuous functions whichare a combination of various continuous functions.

An example of a control parameter in a control function is the desiredvalue (the set point) of the oxygen concentration in a nitrificationtank. Examples of measurement parameters associated with this controlparameter comprise the nitrate concentration, the redox potential andthe phosphate concentration.

The fixed set point of the oxygen concentration in the nitrificationtank forms, e.g. in combination with a measurement value for the sameoxygen concentration, the basis of the selection of a suitable controlaction in the form of an increase or a reduction in the oxygen supply tothe nitrification tank.

Another example of a control parameter of a control function is theactual ammonium concentration in a denitrification tank. Examples ofmeasurement parameters associated with this control parameter comprisethe ammonium concentration, the oxygen concentration and the oxygensupply.

The fixed value for the ammonium concentration may e.g. form the basisof determining whether the operation conditions should be shiftedbetween the nitrification and denitrification tanks during the controlof a purification plant of the type described above in connection withthe disclosure of the article "Computer Control of an AlternatingActivated Sludge Process".

A preferred embodiment of the invention is characterized in that thecontrol parameter is determined on the basis of a weighted combinationof control functions, the control functions being weighted relative totheir suitability in connection with the control action in question.

The use of this embodiment of the invention allows the control functionsused in the determination of the control parameter to be weighteddifferently depending on the magnitude of the parameter.

The control parameter may, e.g., be determined by use of one of thefollowing two formulas: ##EQU1## wherein CP is the determined controlparameter, w are weights, c_(pi) are the control parameter determinedwith the individual control functions and m is a positive integer above1, ##EQU2## wherein CP, w_(i), c_(pi) and m have the meaning definedabove, and wherein n_(i) are real numbers.

Due to the use of the n_(i-) values, formula (2) allows differentweighting of the individual control functions depending on the magnitudeof the control parameter.

The determination of the control parameter using weights for theindividual control functions may further be carried out by using acombination of different continuous functions, such as exponential,logarithmic and potency functions, i.e., using conventional statisticand stocastic models.

The determination of the control parameter and the subsequent selectionof the control action are preferably carried out using a mathematicalmodel for the purification plant which defines the correlation betweenmeasurement parameters, derived measurement parameters and controlparameters and which can describe the state of the purification plant atthe relevant point of time. Alternatively, the control action may bedetermined on the basis of a predetermined set of rules.

Another preferred embodiment of the invention is characterized in thatthe quality of the measurement results is evaluated and that the controlparameter is determined on the basis of the evaluated measurementresults.

The evaluation of the quality of the measurement results is preferablycarried out using the method described in DK patent application No.1677/91 having the title "Method of controlling waste water purificationplants using quality evaluation of measurement data", said applicationbeing filed on the same day as the present application.

Reference is made to the application for a more detailed description ofthe way in which the evaluation of the quality of the measurementresults is carried out in the above-mentioned preferred embodiment ofthe invention.

The quality evaluation of the measurement results is preferably carriedout on the basis of a comparison of the measurement value for at leastone parameter with an expected dynamic value interval calculatedcontinuously on the basis of the mathematical model and a simultaneousand/or previous measurement of one or several other parameters and/or aprevious measurement of the same parameter.

The expected dynamic value interval is preferably determined bycalculation of an expected dynamic value and maximum variationstherefrom.

More preferably, the quality evaluation of the measurement results iscarried out by evaluating the credibility of the measurement value onthe basis of the comparison of the measurement value with the expecteddynamic value interval by the allocation of a credibility factor which,in combination with the measurement value, is used in the subsequentdetermination of the control parameter.

Prior to the determination of the control parameter, the measurementresults may possibly be corrected with a value corresponding to themagnitude of the identifiable measurement interference, if any.

As used herein the term "identifiable measurement interference" meansmeasurement interference caused by influences imposed on thepurification plant in connection with the control of same.

The quantification of the identifiable measurement interference ispreferably carried out on the basis of the mathematical model and pastdata of response courses for control modifications of the same typecarried out previously.

In the above preferred embodiment of the invention, the controlparameter is determined at any time on the basis of the most crediblemeasurement results of those available and by weighting of sameaccording to their credibility, thereby obtaining an optimum controlcompared to the collected material of measurement results, and whichcontrol is far more efficient than the control obtained with the priorart methods.

In this preferred embodiment of the invention, the control parameter isdetermined on the basis of the collected measurement values for two ormore parameters and the control functions and credibility factorsassociated therewith.

In this case the control parameter may e.g. be determined by using oneof the following two formulas: ##EQU3## wherein CP, w_(i), cp_(i) and mhave the meaning defined above, and wherein cf_(i) is a credibilityfactor, ##EQU4## wherein CP, w_(i), cp_(i), cf_(i), n_(i) and m have themeaning defined above.

The method according to the invention is preferably carried out using anintegral control and computer system (control apparatus) collecting andstoring measurement results and control signals, processing thecollected data using a mathematical model and implementing new controlactions.

The waste water purification plant controlled according to the method ofthe invention may be a biological waste water purification plant whereinthe purification is carried out by means of microorganisms.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention will now be described in further details with reference tothe accompanying drawings, wherein

FIG. 1 is a block diagram of general action steps in controlling a wastewater purification plant using a preferred embodiment of the method ofthe invention,

FIG. 2 is a flow diagram of action steps in the quality evaluation andcorrection of a measurement value in a preferred embodiment of themethod according to the invention,

FIG. 3. illustrates an actual example of a control function for ananoxic treatment tank in a given biological waste water purificationplant, and the Figure is a diagrammatical view of the correlationbetween the ammonium concentration (the control parameter) and theoxygen consumption rate (the measurement parameter),

FIGS. 4-6. illustrate actual examples of control functions for anaerobic treatment tank in a given biological waste water purificationplant, and the three Figures are diagrammatical views of the correlationbetween the control parameter (the oxygen concentration) and threerespective measurement parameters.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

The action steps shown in FIG. 1 will now be explained in furtherdetails.

By using various measurement apparatuses, measurements of a number ofparameters are carried out sequentially at different places in the wastewater purification plant, and the measurement data thus obtained arecollected (step 1) in the data base of a control apparatus. Examples ofsuch measurement parameters comprise the concentration of ammonium,nitrate, oxygen, phosphate, cell dry matter and biomass in the untreatedwaste water, at various places in the purification plant and in theeffluent, the amount of supplied untreated waste water and the amount ofthe oxygen supplied to the plant.

Furthermore sequential data are collected in the data base of thecontrol apparatus for a variety of different control parameters (step2), sequential data for a number of parameters (step 3) describing thestate of the purification plant, such as time of the day and flowpattern, and data for the response course of the purification plant(step 4) on control actions previously made.

On the basis of the collected measurement data, derived measurement dataare computed in the control apparatus (step 5), such as the rate ofchange of the oxygen concentration, the oxygen consumption rate and thenitrification and denitrification rate.

On the basis of the data collected during steps 1-5, a qualityevaluation and correction of the measurement data collected in step 1 iscarried out in step 6.

The set of quality evaluated and corrected measurement data obtained instep 6 forms the basis of the determination of the control parameter anda selection of the final control action (step 7).

This step may be carried out using a mathematical model defining thecorrelation between the measurement parameters, the derived measurementparameters and the control parameters and describing the state of thepurification plant at the relevant point of time. Alternatively thecontrol action may be determined on the basis of a predetermined set ofrules.

After the final control action has been selected, it is implemented(step 8). The control apparatus effects the implementation bymodifications of the setting of the control apparatus associated withthe individual control parameters.

With reference to FIG. 2 it will now be explained in further details howthe above-mentioned quality evaluation and correction (step 6) iscarried out.

A given measurement value is initially subjected to a primary evaluation(step 10) comprising investigating whether the measurement value iscomprised within a value interval having fixed and relatively widelimits corresponding to the maximum and minimum, respectively, values ofthe relevant measurement parameter appearing in ordinary operationconditions.

Furthermore, the primary evaluation comprises investigating whether thechange of the measurement value as compared to the latest measurementcarried out is comprised within a value change interval set so as alsoto have fixed and relatively wide limit values corresponding to themaximum values of the relevant measurement parameter appearing inordinary operation conditions.

If the measurement value is not comprised within the above valueinterval, or if the change of the measurement value is not comprisedwithin the above value change interval, the measurement value isrejected as erroneous.

Thus, the primary evaluation serves to discard the evidently erroneousmeasurements.

The state of the waste water purification plant at the time of themeasurement is then identified (step 11), cf. step 3 described above.

In steps 12 and 13 the measurement value is verified, i.e. it isevaluated whether the value is correct or not.

The verification is effected by determining (step 13) whether themeasurement value is comprised within a value interval determined on thebasis of an expected value and maximum deviations therefrom, which maybe computed (step 12) on the basis of the data collected in steps 1-5and the mathematical model quantitatively describing the correlationbetween different parameters.

An example of such calculation of the expected value and maximumdeviations is that the ammonium concentration in a given treatment tankis calculated on the basis of measurements of the amount of waste watersupplied to the plant and the time of the day, providing indirectinformation about the ammonium concentration of the supplied wastewater, and/or the past course for the ammonium concentration in thetreatment tank, and/or the past course for the nitrate concentration inthe treatment tank, and/or the oxygen concentration in the treatmenttank, and the amount of oxygen supplied thereto, together providinginformation about the oxygen consumption rate.

When using several methods to calculate the expected value and maximumdeviations therefrom, the methods are weighted according to theircredibility.

If the measurement value is not comprised within the calculated valueinterval, the deviation of the measurement value from the expected valueis calculated and stored (step 14).

Subsequently, it is investigated whether the measurement value includesidentifiable measurement interference (step 15). Such identifiablemeasurement interference results from modifications made in the state ofthe purification plant in order to control said plant, such asmodifications in the flow pattern of the purification plant by controlof the pump operation and change in the oxygen supply rate to atreatment tank by control of the supply pump.

Such control modifications give rise to a relatively brief change of themeasured parameter, which change of measurement parameter is notsymptomatic of the general state dynamics of the plant.

Consequently, such brief change of the measurement parameter isneglected by correcting the measurement value with a value correspondingto the interference (step 16). The quantification of the interference iscarried out on the basis of the mathematical model and past data of theresponse courses for modifications of the same type previously made,which data are collected and stored in the memory of the controlapparatus.

After the measurement value has been corrected, it is investigated againwhether the corrected measurement value is comprised within the valueinterval computed in step 12.

If it is found in step 16 that the measurement value does not includeany identifiable interference, it is investiagted whether the valueinterval calculation made in step 12 is incorrect (step 17), which e.g.may be the case if sudden changes in the load of the purification plantoccur, i.e. changes in the amount and/or concentration of the wastewater supplied to the plant. Thus, step 17 includes measurement valuesfor further measurement parameters compared to the measurementparameters forming the basis of the value interval calculation made instep 12.

If it is found in step 17 that the state of the purification plant haschanged so that the value interval calculation made in step 12 isincorrect, a revised value interval (step 18) is computed on the basisof the measurement parameters used in steps 12 and 17, which revisedvalue interval is used for comparison with the measurement valueapproved in step 10 and possibly corrected in step 15.

As explained above, initially only measurement results for a limited setof measurement parameters are preferably used in the value intervalcalculation made in step 12, as measurement results for a further set ofmeasurement results are only included, if it is found that themeasurement value is beyond the value interval initially computed. Suchdivision of the verification procedure is preferred in order to limitthe calculation work associated therewith and hence the necessarycomputer capacity.

Alternatively, all the measurement parameters used in steps 12 and 17may be included in the value interval calculation initially made,corresponding to the cancellation of steps 17 and 18 from the flowdiagram shown in FIG. 2.

After the verification and a correction, if any, the measurement valueis evaluated as to credibility (step 19), irrespective of whether saidvalue is comprised within the value interval calculated in steps 12 or18, or not.

Of course measurement values beyond the above mentioned value intervalhave a low credibility and are generally not used in the subsequentselection of the final control action, except in particular situationswhere the measurement results obtained are few or of a poor quality.

The credibility evaluation is effected by comparing said measurementvalue with the value interval computed in step 12 or the revised valueinterval calculated in step 18, and on the basis of the result of thiscomparison by subsequently allotting the measurement value a credibilityfactor which is stored in the data base of the computer system (step20), and using said factor in combination with the possibly correctedmeasurement value for the subsequent selection of the final controlaction.

The invention will now be explained in further detail with reference tothe following example.

EXAMPLE

It is desired to control a biological waste water purification plantcomprising two treatment tanks which are alternately operated in anoxicand aerobic conditions, and wherein the flow pattern is changedaccordingly and so that the untreated waste water is supplied to theanoxic tank (denitrification tank), from which it is carried to theaerobic tank (nitrification tank) and therefrom further on in the plantto a clarification tank, in which a sedimentation of active sludge iscarried out, the sludge subsequently being recycled in the plant forintroduction into the anoxic tank and from which clarification tank theeffluent is dicharged.

The general control strategy comprises two control criteria, viz. 1)shifting the operation state between the two treatment tanks, i.e., achange in the set point of the oxygen concentration in the two tanks anda change in the flow pattern of the plant, if both the nitrateconcentration in the denitrification tank and the ammonium concentrationin the nitrification tank are less than or equal to predeterminedrespective minimum limit values, and 2) controlling the oxygenconcentration during the course of the nitrification and denitrificationphase in the two respective tanks in relation to the desired oxygenconcentration (set point) determined on the basis of measurements ofother parameters.

Control according to control criterium 1) is effected by use of, e.g.,the ammonium concentration in the nitrification tank as controlparameter, and the measurement parameters associated therewith are theoxygen concentration, the oxygen supply and the ammonium concentrationin the same tank.

On the basis of the measurement values for the oxygen concentration ofand the oxygen supply to the aerobic tank, it is possible to compute theoxygen consumption rate in the tank. The change in the oxygenconsumption rate is coupled to the ammonium concentration, and thecorrelation between the two noted parameters, i.e., the control functionused is determined on the basis of past data and experience from earlieroperations and calculations using a mathematical model. The controlfunction is shown in FIG. 3.

Control according to control criterium 2) is effected by use of e.g. theset point of the oxygen concentration in the denitrification tank ascontrol parameter, and the measurement parameters associated therewithcomprise the nitrate concentration, the phosphate concentration and theredox potential in the same tank.

The control functions used for the three measurement parameters aredetermined on the basis of past data and experience from earlieroperations, and the functions will appear from FIGS. 4-6 showing thedesired oxygen concentration measured in mg O₂ per liter as a functionof the nitrate concentration, the rate of change of the phosphateconcentration (calculated on the basis of the phosphate measurements)and the redox potential, respectively.

Control according to control criterium 1) results in a measurement of anammonium concentration in the nitrification tank of 1.5 mg NH₄ --N perliter, and the measured values for the oxygen concentration and theoxygen supply in the same tank are calculated to correspond to a changein the oxygen consumption rate of -0.5 mg O₂ per liter per hour. On thebasis of the control function shown in FIG. 3 it is found that themeasured oxygen consumption rate corresponds to an ammoniumconcentration of 0.9 mg NH₄ --N per liter.

The control functions for the measurement parameter of ammoniumconcentration and the derived measurement parameter of oxygenconsumption rate are allotted the weights 0.8 and 0.2, respectively.

The control parameter, i.e. the ammonium concentration (AC), is thendetermined using the above formula (1): ##EQU5## As the determined valuefor the control parameter is greater than the minimum limit valuecausing a shift in the operation conditions between the two treatmenttanks, no such shift is effected.

Control according to control criterium 2) results in a measurement of anitrate concentration in the denitrification tank of 0.5 mg NO₃ --N. perliter and a redox potential of 90 mV, and on the basis of measurementsof the phosphate concentration in the same tank the rate of change ofthe phosphate concentration is calculated to amount to 2 g PO₄ --P perm³ per hour. On the basis of the control functions shown in FIGS. 4-6,three different values for the set point of the oxygen concentration arefound, viz. 0.2 mg O₂ per liter, 0 mg O₂ per liter and 0.7 mg O₂ perliter, respectively.

The control functions for the measurement parameter of nitrateconcentration, the derived measurement parameter of rate of change ofthe phosphate concentration and the measurement parameter of redoxpotential are allotted the weights 7, 5 and 3, respectively.

The control parameter, i.e. the set point of the oxygen concentration(SOC), is then determined using the above formula (1): ##EQU6## On thebasis of the determined control parameter, a control action can now beselected, causing the oxygen concentration in the denitrification tankto be raised from the previous 0 mg O₂ per liter to 0.23 mg O₂ perliter. This increase in the oxygen concentration expresses the fact thatthe information contained in the measurement values used for the threemeasurement parameters indicates that the nitrate concentration is lessthan the minimum limit value causing a shift in the operation state tobe effected, and that the set point of the oxygen concentrationtherefore may be slightly raised to allow reaction of ammonium duringthe period up to the point of time where a shift in the operation statebetween the tanks is carried out. Consequently, an improved utilizationof the volume capacity of the plant and a more efficient purification ofthe waste water are obtained.

Furthermore, the above control procedure results in a very quick andreliable identification of the state of the denitrification tank andhence a more efficient control of the same.

I claim:
 1. A method of automatically controlling a waste waterpurification plant comprising the steps of measuring at least one systemparameter, determining a control parameter on the basis of themeasurement results obtained and a selected control function, selectinga control action on the basis of the determined control parameter, andsubsequently implementing the selected control action, wherein thecontrol parameter is determined on the basis of the measurement resultsfor at least two parameters and the control functions associated withsaid parameters.
 2. A method according to claim 1, wherein the controlparameter is determined on the basis of a weighted combination of thecontrol functions, the control functions being weighted in relation totheir suitability in connection with the control action in question. 3.A method according to claim 2, wherein the control functions used indetermining the control parameter are weighted differently depending onthe magnitude of the control parameter.
 4. A method according to claim1, wherein the determination of the control parameter and the subsequentselection of the control action are carried out using a mathematicalmodel for the purification plant.
 5. A method according to claim 4,wherein the quality of the measurement results is evaluated and that thedetermination of the control parameter is effected on the basis of thesaid evaluated measurement results.
 6. A method according to claim 5,wherein the quality is evaluated on the basis of a comparison of themeasurement value for at least one parameter with an excepted dynamicvalue interval calculated continuously on the basis of the mathematicalmodel and a simultaneous measurement of at least one other parameter. 7.A method according to claim 6, wherein the expected dynamic valueinterval is determined by calculation of an expected dynamic value andmaximum deviations therefrom.
 8. A method according to claim 6, whereinthe credibility of the measurement value is evaluated on the basis ofthe comparison of the measurement value with the expected dynamic valueinterval by the allocation of a credibility factor which, in combinationwith the measurement value, is used in the subsequent determination ofthe control parameter.
 9. A method according claim 1, wherein prior tothe selection of the control action the measurement results arecorrected with a value corresponding to the size of the identifiablemeasurement interference.
 10. A method according to claim 9, wherein thequantification of the identifiable measurement interference is effectedon the basis of the mathematical model and past data of response coursesfor control modifications of the same type previously made.
 11. A methodaccording to claim 1, wherein using an integral control and computersystem (control apparatus) collecting and storing measurement resultsand control signals, processing the collected data using themathematical model and implementing new control actions.
 12. A methodaccording to claim 1, wherein the controlled waste water purificationplant is a biological waste water purification plant in which thepurification is carried out by means of microorganisms.
 13. A methodaccording to claim 5, wherein the quality is evaluated on the basis of acomparison of the measurement value for at least one parameter with anexpected dynamic value interval calculated continuously on the basis ofthe mathematical model and a prior measurement of at least one otherparameter.
 14. A method according to claim 5, wherein the quality isevaluated on the basis of a comparison of the measurement value for atleast one parameter with an expected dynamic value interval calculatedcontinuously on the basis of the mathematical model and both asimultaneous and a prior measurement of at least one other parameter.15. A method according to claim 5, wherein the quality is evaluated onthe basis of a comparison of the measurement value for at least oneparameter with an expected dynamic value interval calculatedcontinuously on the basis of the mathematical model and priormeasurement of the same parameter.